class_docstr: Decision List Classifier
  
  Currently a slight variant of SkopeRules from skope-rules.
  https://github.com/scikit-learn-contrib/skope-rules
code: def _extract_rules(self, rules):
      rules = deepcopy(rules)
      rules = list(sorted(rules, key=lambda x: x[1][0], reverse=True))
  
      rule_li = []
      prec_li = []
      recall_li = []
      predict_li = []
      features_dict = {feat: [] for feat in self.feature_names_in_}
  
      def extract_orig_features(pattern, rule):
          feature_set = set()
          for m in re.finditer(pattern, rule):
              orig_feature = self.feature_map_[m.group(1)]
              feature_set.add(orig_feature)
          return feature_set
  
      pattern = "(" + _BASE_FEATURE_NAME + "[0-9]+)"
      for indx, rule_rec in enumerate(rules):
          rule = rule_rec[0]
          rule_round = " ".join(
              [
                  "{0:.2f}".format(float(x))
                  if x.replace(".", "", 1).isdigit()
                  else x
                  for x in rule.split(" ")
              ]
          )
          feature_set = extract_orig_features(pattern, rule_round)
          rule_fix = re.sub(
              pattern,
              lambda m: self.feature_map_[m.group(1)],
              rule_round,
          )
          rule_li.append(rule_fix)
          prec_li.append(rule_rec[1][0])
          recall_li.append(rule_rec[1][1])
          predict_li.append(1.0)
  
          for feat in feature_set:
              features_dict[feat].append(indx)
  
      # Provide default rule
      rule_li.append("No Rules Triggered")
      prec_li.append(self.pos_ratio_)
      recall_li.append(1.0)
      predict_li.append(0.0)
  
      return rules, rule_li, prec_li, recall_li, features_dict
  
imports: from itertools import count
  from sklearn.base import ClassifierMixin
  from sklearn.utils.validation import check_is_fitted
  from ..api.base import ExplainerMixin, ExplanationMixin
  from ..utils._explanation import gen_name_from_class, gen_global_selector, gen_local_selector, gen_perf_dicts
  from copy import deepcopy
  import numpy
  import pandas
  import re
  from ..utils._clean_x import preclean_X
  from ..utils._clean_simple import clean_dimensions, typify_classification
  from ..utils._unify_data import unify_data
  import logging
label_desc: Use image node_id 6 for calling the DecisionListClassifier obj's underlying member method code with example usage: obj._extract_rules(rules) and returns: rules,  rule_li,  prec_li,  recall_li,  features_dict, feature_set